Document Detail

Fast algorithm for relaxation processes in big-data systems.
MedLine Citation:
PMID:  25375619     Owner:  NLM     Status:  Publisher    
Relaxation processes driven by a Laplacian matrix can be found in many real-world big-data systems, for example, in search engines on the World Wide Web and the dynamic load-balancing protocols in mesh networks. To numerically implement such processes, a fast-running algorithm for the calculation of the pseudoinverse of the Laplacian matrix is essential. Here we propose an algorithm which computes quickly and efficiently the pseudoinverse of Markov chain generator matrices satisfying the detailed-balance condition, a general class of matrices including the Laplacian. The algorithm utilizes the renormalization of the Gaussian integral. In addition to its applicability to a wide range of problems, the algorithm outperforms other algorithms in its ability to compute within a manageable computing time arbitrary elements of the pseudoinverse of a matrix of size millions by millions. Therefore our algorithm can be used very widely in analyzing the relaxation processes occurring on large-scale networked systems.
S Hwang; D-S Lee; B Kahng
Related Documents :
7171639 - The extended branch-arrow model of the formation of retino-tectal connections.
17357989 - Regression b-spline smoothing in bayesian disease mapping: with an application to patie...
25152899 - Semi-supervised learning of statistical models for natural language understanding.
10838009 - "true" color surface anatomy: mapping the visible human to patient-specific ct data.
25235909 - The songsmith story, or how a small-town hidden markov model dade it to the big time.
11736069 - Parameter estimation in spatially extended systems: the karhunen-lóeve and galerkin mul...
20369919 - Partial differential equations-based segmentation for radiotherapy treatment planning.
21146909 - Measuring and valuing productivity loss due to poor health: a critical review.
21997329 - Determining posture from physiological tremor.
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2014-10-6
Journal Detail:
Title:  Physical review. E, Statistical, nonlinear, and soft matter physics     Volume:  90     ISSN:  1550-2376     ISO Abbreviation:  Phys Rev E Stat Nonlin Soft Matter Phys     Publication Date:  2014 Oct 
Date Detail:
Created Date:  2014-11-6     Completed Date:  -     Revised Date:  2014-11-7    
Medline Journal Info:
Nlm Unique ID:  101136452     Medline TA:  Phys Rev E Stat Nonlin Soft Matter Phys     Country:  -    
Other Details:
Languages:  ENG     Pagination:  043303     Citation Subset:  -    
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Previous Document:  Boundary-controlled barostats for slab geometries in molecular dynamics simulations.
Next Document:  Nonergodicity of the Nose-Hoover chain thermostat in computationally achievable time.